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The genetic code has a high level of error robustness. Using values of hydrophobicity scales as a proxy for amino acid character, and the Mean Square measure as a function quantifying error robustness, a value can be obtained for a genetic…

Populations and Evolution · Quantitative Biology 2013-09-19 Harry Buhrman , Peter T. S. van der Gulik , Gunnar W. Klau , Christian Schaffner , Dave Speijer , Leen Stougie

Single individual haplotyping is an NP-hard problem that emerges when attempting to reconstruct an organism's inherited genetic variations using data typically generated by high-throughput DNA sequencing platforms. Genomes of diploid…

Machine Learning · Computer Science 2019-09-04 Somsubhra Barik , Haris Vikalo

Our goal in this paper is to automatically extract a set of decision rules (rule set) that best explains a classification data set. First, a large set of decision rules is extracted from a set of decision trees trained on the data set. The…

Neural and Evolutionary Computing · Computer Science 2022-09-19 Paul-Amaury Matt , Rosina Ziegler , Danilo Brajovic , Marco Roth , Marco F. Huber

We propose a genetic-algorithm-based method to find the unitary transformations for any desired quantum computation. We formulate a simple genetic algorithm by introducing the "genetic parameter vector" of the unitary transformations to be…

Quantum Physics · Physics 2015-01-08 Jeongho Bang , Seokwon Yoo

In Search Based Software Engineering, Genetic Programming has been used for bug fixing, performance improvement and parallelisation of programs through the modification of source code. Where an evolutionary computation algorithm, such as…

Neural and Evolutionary Computing · Computer Science 2012-11-22 Brendan Cody-Kenny , Stephen Barrett

This article seeks to encourage a mathematical dialog regarding a possible solution to Beals Conjecture. It breaks down one of the worlds most difficult math problems into laymans terms and encourages people to question some of the most…

History and Overview · Mathematics 2015-01-12 Angela Moore

Genetic algorithms are considered as an original way to solve problems, probably because of their generality and of their "blind" nature. But GAs are also unusual since the features of many implementations (among all that could be thought…

Artificial Intelligence · Computer Science 2011-08-24 Jean-Louis Dessalles

The yearly global production of data is growing exponentially, outpacing the capacity of existing storage media, such as tape and disk, and surpassing our ability to store it. DNA storage - the representation of arbitrary information as…

Quantitative Methods · Quantitative Biology 2023-10-04 Thomas Heinis , Roman Sokolovskii , Jamie J. Alnasir

We develop topological methods for analyzing difference topology experiments involving 3-string tangles. Difference topology is a novel technique used to unveil the structure of stable protein-DNA complexes involving two or more DNA…

Geometric Topology · Mathematics 2016-01-20 Isabel K. Darcy , John Luecke , Mariel Vazquez

An alternative computational approach to the Collatz (3n+1) conjecture is presented that may be theoretically capable of confirming the conjecture.

Number Theory · Mathematics 2011-07-25 Kevin P. Thompson

The scarcity of molecules with desirable properties (i.e., `positive' molecules) is an inherent bottleneck for generative molecule design. To sidestep such obstacle, here we propose molecular task arithmetic: training a model on diverse and…

Machine Learning · Computer Science 2025-12-09 Rıza Özçelik , Sarah de Ruiter , Francesca Grisoni

Refining an existing counting argument, we provide an improved upper bound for the number of 1324-avoiding permutations of a given length.

Combinatorics · Mathematics 2014-04-16 Miklós Bóna

Many proofs in discrete mathematics and theoretical computer science are based on the probabilistic method. To prove the existence of a good object, we pick a random object and show that it is bad with low probability. This method is…

Information Theory · Computer Science 2017-08-01 Pat Morin , Wolfgang Mulzer , Tommy Reddad

A random-key genetic algorithm is an evolutionary metaheuristic for discrete and global optimization. Each solution is encoded as a vector of N random keys, where a random key is a real number randomly generated in the continuous interval…

Neural and Evolutionary Computing · Computer Science 2026-01-13 Mariana A. Londe , Luciana S. Pessoa , Carlos E. Andrade , José F. Gonçalves , Mauricio G. C. Resende

Molecular evidence regarding the genetic code has been examined and the findings on the nature of the early events responsible for the amino acid distribution in the code are reported.

Biological Physics · Physics 2007-05-23 Brian K. Davis

Ultrametric approach to the genetic code and the genome is considered and developed. $p$-Adic degeneracy of the genetic code is pointed out. Ultrametric tree of the codon space is presented. It is shown that codons and amino acids can be…

Other Quantitative Biology · Quantitative Biology 2017-05-16 Branko Dragovich , Andrei Yu. Khrennikov , Nataša Ž. Mišić

In this paper, we introduce a graph matching method that can account for constraints of arbitrary order, with arbitrary potential functions. Unlike previous decomposition approaches that rely on the graph structures, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2018-02-26 D. Khuê Lê-Huu , Nikos Paragios

Current Y chromosome research is limited in the poor resolution of Y chromosome phylogenetic tree. Entirely sequenced Y chromosomes in numerous human individuals have only recently become available by the advent of next-generation…

Populations and Evolution · Quantitative Biology 2013-10-25 Chuan-Chao Wang , Hui Li

We present an approach for regression problems that employs analytic continued fractions as a novel representation. Comparative computational results using a memetic algorithm are reported in this work. Our experiments included fifteen…

Neural and Evolutionary Computing · Computer Science 2021-06-17 Pablo Moscato , Haoyuan Sun , Mohammad Nazmul Haque

Is it possible to understand cancer? Or more specifically, is it possible to understand cancer from genetic side? There already many answers in literature. The most optimistic one has claimed that it is mission-possible. Duesberg and his…

Subcellular Processes · Quantitative Biology 2008-11-26 P. Ao
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